remove main.py from remote repo

RAG/main.py

@@ -1,83 +0,0 @@
-import time
-import pandas as pd
-import os
-from dotenv import load_dotenv
-from config import (
-    current_dir, CSV_FILE, system_prompt, 
-    EMBEDDINGS_FILE, FAISS_INDEX_FILE
-)
-from langchain.globals import set_llm_cache
-from langchain_community.cache import SQLiteCache
-from embeddings import load_embeddings
-from rag_chain import simple_rag_prompt, calculate_similarity, get_context
-
-
-# Load environment variables
-load_dotenv('environment.env')
-
-# Set up cache
-set_llm_cache(SQLiteCache(database_path=".langchain.db"))
-
-def main():
-    # Number of questions to test
-    n = 10
-    
-    # Load embeddings and index
-    embeddings, docs, df, index = load_embeddings()
-    
-    # Define retrieval chain
-    retrieval_chain = lambda q: get_context(q, index, docs)
-    
-    # Load questions from CSV
-    csv_path = os.path.join(current_dir, CSV_FILE)
-    qa_df = pd.read_csv(csv_path)
-    
-    # Output file
-    output_file = 'rag_output.txt'
-    
-    with open(output_file, 'w', encoding='utf-8') as f:
-        for i in range(n):  
-            try:
-                question = qa_df.iloc[i]['question']
-                original_answer = qa_df.iloc[i]['answer']
-                
-                print(f"Processing question {i+1}: {question}")
-                
-                start_time = time.time()
-                rag_answer, similarity_score = simple_rag_prompt(retrieval_chain, question)
-                end_time = time.time()
-                
-                response_time = end_time - start_time
-                # answer_similarity = calculate_similarity(original_answer, rag_answer)
-
-                # Check if rag_answer is a string before calculating similarity
-                if isinstance(rag_answer, str):
-                    answer_similarity = calculate_similarity(original_answer, rag_answer)
-                else:
-                    answer_similarity = 0
-                    print(f"Warning: RAG answer for question {i+1} is not a string. Answer: {rag_answer}")
-                
-                # Write results to file
-                f.write(f"Question {i+1}: {question}\n")
-                f.write(f"Original Answer: {original_answer}\n")
-                f.write(f"RAG Answer: {rag_answer}\n")
-                f.write(f"Response Time: {response_time:.2f} seconds\n")
-                f.write(f"Retrieval Similarity Score: {similarity_score:.4f}\n")
-                f.write(f"Answer Similarity Score: {answer_similarity:.4f}\n")
-                f.write("-" * 50 + "\n")
-                
-                f.flush()
-                print(f"Processed question {i+1}")
-                
-                # Add a small delay to avoid rate limiting
-                time.sleep(1) 
-            except Exception as e:
-                print(f"Error processing question {i+1}: {str(e)}")
-                f.write(f"Error processing question {i+1}: {str(e)}\n")
-                f.write("-" * 50 + "\n")
-                f.flush()
-    
-    print(f"Output has been saved to {output_file}")
-
-if __name__ == "__main__":
-    main()